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Item Open Access Unifying nucleation and crystal growth mechanisms in membrane crystallisation(Elsevier, 2025-05-01) Mapetere, A.; Di Profio, Gianluca; Curcio, Efrem; Campo Moreno, Pablo; McAdam, Ewan J.While several mechanisms have been proposed to describe crystallisation processes in membrane distillation, it has not been possible to provide a definitive description since the nucleation kinetics are difficult to measure. This study therefore introduced non-invasive techniques to measure induction time within two discrete domains (the membrane surface and bulk solution) and was complemented by the introduction of a modified power law relation between supersaturation and induction time, that enables mass and heat transfer processes in the boundary layer to be directly related to classical nucleation theory (CNT). Temperature (T, 45–60 °C) and temperature difference (ΔT, 15–30 °C) were used to adjust boundary layer properties, which established a log-linear relation between the nucleation rate and the supersaturation level in the boundary layer at induction, which is characteristic of CNT. Crystal size distribution analysis demonstrated how nucleation rate and crystal growth rate could be adjusted using ΔT and T respectively. Consequently, ΔT and T can be used collectively to fix the supersaturation set point within the boundary layer to achieve the preferred crystal morphology. However, at higher supersaturation levels, scaling was observed. Discrimination of the primary nucleation mechanisms, using measured induction times, revealed scaling to be formed homogeneously, which indicates exposure of the pores to extremely high supersaturation levels. Morphological analysis of scaling indicated growth to be dominated by secondary nucleation mechanisms, that resulted in a habit that is distinctive from the crystal phase formed in the bulk solution. From this analysis, a critical supersaturation threshold was identified, below which kinetically controlled scaling can be ‘switched-off’, leaving crystals to form solely in the bulk solution comprising the preferred cubic morphology. This study serves to unify understanding on nucleation and growth mechanisms to enhance control over crystallisation in membrane systems.Item Open Access Artificial intelligence-driven innovation in Ganoderma spp.: potentialities of their bioactive compounds as functional foods(Royal Society of Chemistry (RSC), 2025) Khanal, Sonali; Sharma, Aman; Pillai, Manjusha; Thakur, Pratibha; Tapwal, Ashwani; Kumar, Vinod; Verma, Rachna; Kumar, DineshGanoderma spp., which are essential decomposers of lignified plant materials, can affect trees in both wild and cultivated settings. These fungi have garnered significant global interest owing to their potential to combat several chronic, complicated, and infectious diseases. As technology progresses, researchers are progressively employing artificial intelligence (AI) for studying various fungal strains. This novel approach has the potential to accelerate the knowledge and application of Ganoderma spp. in the food industry. The development of extensive Ganoderma databases has markedly expedited research on them by enhancing access to information on bioactive components of Ganoderma and promoting collaboration with the food sector. Progress in AI techniques and enhanced database quality have further advanced AI applications in Ganoderma research. Techniques such as machine learning (ML) and deep learning employing various methods, including support vector machines (SVMs), Bayesian networks, artificial neural networks (ANNs), random forests (RFs), and convolutional neural networks (CNNs), are propelling these advancements. Although AI possesses the capacity to transform Ganoderma research by tackling significant difficulties, continuous investment in research, data dissemination, and interdisciplinary collaboration are necessary. AI could facilitate the development of customized functional food products by discerning patterns and correlations in customer data, resulting in more specific and accurate solutions. Thus, the future of AI in Ganoderma research looks auspicious, presenting prospects for ongoing advancement and innovation in this domain.Item Open Access On the role of crystal-liquid interfacial energy in determining scaling, nucleation and crystal growth in membrane distillation crystallisation(Elsevier, 2025-05-01) Vasilakos, Konstantinos; Thomas, Navya; Hermassi, Mehrez; Campo Moreno, Pablo; McAdam, Ewan J.While the interfacial energy (σ) of a solute contributes toward the excess surface free energy requirement for nucleation, its role in determining scaling, nucleation and crystal growth processes within membrane distillation has yet to be described. Highly soluble salts (low σ) are generally understood to possess a low nucleation energy, where the limited relative supersaturation (Δc/c∗) can favour a heterogeneous primary nucleation mechanism. This was indicated by scaling, which is generally presumed to occur in response to the membrane substrate lowering the critical Gibbs free energy requirement for nucleation (ΔG∗). For less soluble salts (high σ), primary nucleation was not observed until Δc/c∗ exceeded a threshold of 1. It was postulated that the excess chemical potential available was sufficient to favour homogeneous primary nucleation in the bulk solution, which mitigates scale formation on the membrane. In-situ characterisation methods also established how nucleation rate and crystal size could be directly attributed to the σ, which is compatible with the crystallisation literature on aqueous salts within a comparable range of solubilities. While crystallisation tends to be controlled by a combination of thermodynamic and kinetic processes, this study illustrates how interfacial energy (a thermodynamic quantity) can be used to anticipate nucleation and crystal growth mechanisms in membrane crystallisation.Item Open Access Rivers as natural capital assets: a quick scoping review to assess the evidence linking river asset condition to changes in the flow of ecosystem services(Wiley, 2025) Zini, Valentina; Johnson, Natalie; Crouch, Alice; Lenagan, Gerard; Cooper, Chris; Naura, Marc; Speck, Imogen; Rouquette, JimRiver managers are beginning to adopt natural capital approaches in practice. However, while it is crucial for river management, the link between river asset condition and the flow of ecosystem services is poorly understood. In this study, we conducted a Quick Scoping Review (QSR) of the research into river asset condition and ecosystem service delivery to explore the current state of knowledge. The review team developed a PICO (Population, Intervention, Control, Outcome) model to transpose the concepts of the research enquiry into a search strategy for the evidence base and used a Delphi screening exercise to prioritise a subset of literature for the narrative findings. VOSviewer was used to analyse the high‐level linguistic themes from the full list of references. This co‐designed, collaborative and objective QSR approach allowed us to examine a large body of literature in a reproducible manner while minimising bias, demonstrating best practice for evidence review that should be continuously updated, generating a ‘living evidence’ knowledge asset. The results of the review demonstrate there is some knowledge of the mechanisms linking the condition of river assets to the delivery of ecosystem services for the majority of the broad range of ecosystem services analysed, with the exception of some of the cultural services, where comparatively fewer studies explore this link. However, a clear understanding of the quantitative evidence of the relationships between condition and ecosystem service delivery is missing for all of the ecosystem services. This gap stems from a lack of standardised methodologies used across the studies and a focus on a narrow range of definitions of condition. The gap needs to be addressed in future research on the topic, and a first step is to adopt more standardised indicators of river asset condition.Item Open Access Robustness and resilience of different solid-liquid separation technologies for tertiary phosphorus removal to low levels by coagulation(Elsevier, 2025-04-25) Murujew, Olga; Wilson, Andrea; Vale, Peter C. J.; Bajón Fernández, Yadira; Jefferson, Bruce; Pidou, MarcIn this study, three tertiary solid separation technologies were assessed on their robustness and resilience against an effluent phosphorus target of <0.3 mg P/L at steady state and dynamic conditions. The ballasted flocculation system was found to be very robust at delivering the low P target. Alternatively, cloth filtration provided a more sustainable option for less strict consents of sub 0.5 mg P/L. The effluent from the membrane system was more variable but it was shown to meet the low consents even with increased phosphorus and solids content in the feed. A molar ratio of 1.37 Fe: P was shown to be sufficient to meet the P target at short contact times as with the ballasted flocculation process. It was highlighted that optimisation of up-stream flocculation can be a considerable factor for consistent performance. Overall, the study determined key attributes of the different technologies tested providing valuable insights for technology selection at full scale.Item Open Access Precision laser manufacturing and metrology of nature-inspired bioactive surfaces for antibacterial medical implants(Elsevier, 2025-04-01) Hawi, Sara; Goel, Saurav; Kumar, Vinod; Giusca, Claudiu; Pearce, Oliver; Ayre, Wayne NishioFemtosecond laser ablation presents a highly promising method to create bioactive nano/micro-structured metallic surfaces, offering numerous avenues for fabricating diverse types of surface structures. However, the relationship between surface properties and biological functionality, leading to the observed bioactivity remains unclear. This study aimed to investigate the relationship between structured/patterned steel surfaces and bioactivity, identifying key factors that enhance their performance. As opposed to the commonly used controversial parameter, arithmetic surface roughness (Ra), fractal dimension analysis was discovered to be strongly representative in quantifiably evaluating the adhesion of Staphylococcus aureus NCTC 7791 and MG-63 osteoblast-like cells. Surface chemistry and surface energy of structured surfaces showed no significant influence on bacterial adhesion. A specific type of laser-induced periodic structured surfaces with sub-micron wavelengths, high fractal dimension, and high texture aspect ratio demonstrated a 63 % reduction in bacterial adhesion compared to flat surfaces while avoiding cytotoxicity to MG-63 cells. Our findings underline the importance of scale-dependent analysis and the use of fractal analysis in evaluating the effectiveness of laser-structured surfaces for orthopaedic implant applications.Item Open Access Peanut value chain development: the case of Lower Lake Victoria Basin of Kenya(MDPI, 2025-03-25) Odunga, George Okoth; Bidzakin, John K.; Okaka, Philip; Okoth, Sheila; Mutsotso, Beneah; Graves, Anil R.Peanut is Kenya’s second most important legume after beans, primarily grown in the Nyanza and Western regions. This study maps the peanut value chain in Kenya, aiming to identify key actors, quantify costs and value addition, and outline constraints and opportunities, with a view to upgrading the chain. A cross-sectional survey was conducted among value chain actors in Karachuonyo and Nyakach sub-counties, complemented by secondary data sources. Descriptive statistics were used to analyze socio-economic characteristics, production volumes, pricing, demand trends, and policy-related factors. The findings indicate a predominance of female farmers (68%) in peanut production, though few use improved technologies; only 26% were aware of improved seed varieties, and just 1.5% reported using them. Fertilizer usage was absent, attributed to high costs, soil conditions, and limited knowledge. The wholesale and processing segments are male-dominated, largely due to capital intensity and travel requirements, while female traders dominate the retail sector. Strengths Weaknesses Opportunity and Threats (SWOT) analysis highlighted the significant potential of favorable production ecologies, processing options, and robust demand in local and international markets. Key constraints identified include limited seed availability, high fertilizer costs, pest issues, and declining soil fertility. Policy implications include increasing access to affordable inputs, promoting gender-inclusive programs, investing in agricultural research and infrastructure, supporting sustainable farming practices, and fostering public-private partnerships to expand processing and market access.Item Open Access Engineering biology applications for environmental solutions: potential and challenges(Springer Nature, 2025-04) Lea-Smith, David J.; Hassard, Francis; Coulon, Frederic; Partridge, Natalie; Horsfall, Louise; Parker, Kyle D. J.; Smith, Robert D. J.; McCarthy, Ronan R.; McKew, Boyd A.; Gutierrez, Tony; Kumar, Vinod; Dotro, Gabriella; Yang, Zhugen; Curtis, Thomas P.; Golyshin, Peter; Heaven, Sonia; Jefferson, Bruce; Jeffrey, Paul; Jones, Davey L.; Le Corre Pidou, Kristell; Liu, Yongqiang; Lyu, Tao; Smith, Cindy; Yakunin, Alexander; Zhang, Yue; Krasnogor, NatalioEngineering biology applies synthetic biology to address global environmental challenges like bioremediation, biosequestration, pollutant monitoring, and resource recovery. This perspective outlines innovations in engineering biology, its integration with other technologies (e.g., nanotechnology, IoT, AI), and commercial ventures leveraging these advancements. We also discuss commercialisation and scaling challenges, biosafety and biosecurity considerations including biocontainment strategies, social and political dimensions, and governance issues that must be addressed for successful real-world implementation. Finally, we highlight future perspectives and propose strategies to overcome existing hurdles, aiming to accelerate the adoption of engineering biology for environmental solutions.Item Open Access An analysis of factors that influence the spatial pattern of faecal matter flow in unsewered cities(Elsevier, 2025-05-25) Sultana, M. Sufia; Waine, Toby W.; Bari, Niamul; Tyrrel, SeanThe management of sanitation systems in unsewered cities in low and middle income countries is a critical issue, yet it is unclear where the risk hotspots are and where interventions should be focused. This study utilised a prototype model, developed by the authors, to map the spatial pattern of faecal flow in Rajshahi city, a secondary city in northwest Bangladesh with a population around a million. This city serves as a representative example of 60 such secondary cities in Bangladesh and hundreds more in the economically developing region in Asia, Africa and Latin America. The model relies on assumptions that carry significant uncertainties; hence, the study employed a sensitivity analysis with multiple plausible scenarios to characterise these uncertainties, aiming to identify ways to improve the model further. Five major influencing factors on the spatial pattern of faecal flow were identified: the emptying of septic tanks, the use of soak pits, and sludge removal from drains, variations in faecal matter production by building types, and the presence or absence of toilets. These factors were shown to collectively have a significant impact (almost 50 % changed) on the model outcome, depending upon the assumptions made. The study offers insights that will guide future data collection efforts by emphasising the need to understand these specific influencing factors and their spatial pattern. Consequently, this research has broader implications for urban sanitation management as well as associated public health research like wastewater surveillance, risk assessment, and disease dynamics in similar urban settings, offering insights into areas of uncertainty that need to be addressed in future modelling efforts.Item Open Access Investigation on the protection ability of two commonly packaging methods to apples during express transportation(Elsevier, 2025-03-01) Yu, Jincheng; Qiang, Hongli; Shi, Mingwei; Li, Zhiguo; Fadiji, Tobi; Wani, Ali Abas; Burgeon, ClémentPackaging plays a vital role in the post-harvest sales process of apples. This study conducted express transportation tests to evaluate the protective effectiveness of two commonly used packaging methods for apples. Key parameters assessed included real-time changes in temperature, humidity, vibration load, and CO₂ levels inside the packaging boxes during transit, as well as the storage quality of apples after transportation. Results showed significant variations in load distribution within corrugated partition-based cardboard boxes (CP combination packaging). Conversely, foam holder-based cardboard boxes (FP combination packaging) exhibited CO₂ accumulation. Furthermore, mechanical damage was predominantly localized to the fruit belly. Compared to CP combination packaging box, FP combination packaging box provided more stable shock resistance at lower vibration forces (< 10 N) across transit routes, likely due to its EPS foam design, which restricted fruit movement and absorbed external vibrations. Post-storage analysis showed that damaged apples experienced a 0.16 % increase in mass loss, a 0.83 % rise in soluble solids content (SSC), and a 0.19 MPa reduction in firmness compared to undamaged controls. These findings provide valuable insights into optimizing packaging design to minimize transport-induced damage and enhance apple preservation.Item Open Access Municipal wastewater treatment with anaerobic membrane Bioreactors for non-potable reuse: a review(Taylor & Francis, 2024-05-18) Huang, Yu; Jeffrey, Paul; Pidou, MarcAnaerobic membrane bioreactors (AnMBRs) are seen as a promising technology for application in water reuse schemes. However, the evidence base for their potential and efficacy in this regard is fragmented. We draw together this disparate knowledge base to offer a state of the art review of municipal wastewater treatment with AnMBRs and evaluate the technology’s potential application for water reuse. Water quality regulations and standards from different regions of the world are used as performance metrics to compare and contrast the treatment performance of pilot and laboratory scale AnMBR systems reported in the literature (n = 50). Findings indicate that under stable operation, AnMBRs have the potential to produce water for agricultural reuse. However, without post-treatment, AnMBRs are incapable of delivering water that meets other non-potable reuse standards across a range of important parameters such as COD, BOD5, NH3-N and TP. Analysis of key operational parameters determine the operation of AnMBR for non-potable reuse purpose cover influent water matrix, pH, temperature, hydraulic retention time, system and membrane configuration. An assessment of candidate post-treatment technologies suggests a tradeoff between the cost and effluent quality based on the reuse application requirement. We conclude by discussing a number of challenges and limitations to the use of AnMBRs for reuse applications in order to outline a pathway to maturity for effective treatment trains.Item Open Access Artificial intelligence for prediction of shelf-life of various food products: recent advances and ongoing challenges(Elsevier, 2025-05-01) Rashvand, Mahdi; Ren, Yuqiao; Sun, Da-Wen; Senge, Julia; Krupitzer, Christian; Fadiji, Tobi; Miró, Marta Sanzo; Shenfield, Alex; Watson, Nicholas J.; Zhang, HongweiBackground: Accurate estimation of shelf-life is essential to maintain food safety, reduce wastage, and improve supply chain efficiency. Traditional methods such as microbial and chemical analysis, and sensory evaluation provide reproducible results but require time and labor and may not be suitable for real-time or high-throughput applications. The integration of artificial intelligence (AI) with advanced analysis techniques offers a suitable alternative for rapid, data-driven estimation of shelf-life in dynamic storage environments. Approach and scope: The current review assesses the application of AI-based techniques such as machine learning (ML), deep learning (DL), and hybrid approaches in food product shelf life prediction. This study highlights how AI can be utilized to examine data from non-destructive testing methods like hyperspectral imaging, spectroscopy, machine vision, and electronic sensors to enhance predictive performance. The review also describes how AI-based techniques contribute to managing food quality, reduce economic losses, and enhance sustainability by ensuring optimized food distribution and reducing waste. Key findings and conclusions: AI techniques overcome conventional techniques by considering intricate, multi-sourced information capturing microbiological, biochemical, and environmental factors influencing food spoilage. Meat, dairy, fruits and vegetables, and beverage case studies illustrate AI techniques' superiority in real-time monitoring and quality assessment. It also identifies limitations such as data availability, model generalizability, and computational cost, constraining extensive applications. Cloud and Internet of Things (IoT) platform integration into future applications has to be considered to enable real-time decision-making and adaptive modeling. AI can be a paradigm-changing tool in food industries with intelligent, scalable, and low-cost interventions in food safety, waste reduction, and sustainability.Item Open Access Enhancing process monitoring and control in novel carbon capture and utilization biotechnology through artificial intelligence modeling: an advanced approach toward sustainable and carbon-neutral wastewater treatment(Elsevier, 2025-05) Cairone, Stefano; Oliva, Giuseppina; Romano, Fabiana; Pasquarelli, Federica; Mariniello, Aniello; Zorpas, Antonis A.; Pollard, Simon J. T.; Choo, Kwang-Ho; Belgiorno, Vincenzo; Zarra, Tiziano; Naddeo, VincenzoIntegrating carbon capture and utilization (CCU) technologies into wastewater treatment plants (WWTPs) is essential for mitigating greenhouse gas (GHG) emissions and enhancing environmental sustainability, but further advancements in process monitoring and control are critical to optimizing treatment performance. This study investigates the application of artificial intelligence (AI) modeling to enhance process monitoring and control in a novel integrated CCU biotechnology with a moving bed biofilm reactor (MBBR) sequenced with an algal photobioreactor (aPBR). This system reduces GHG and odour emissions simultaneously. Several machine learning (ML) models, including artificial neural networks (ANNs), support vector machines (SVM), random forest (RF), and least-squares boosting (LSBoost), were tested. The LSBoost was the most suitable for modeling the MBBR + aPBR system, exhibiting the highest accuracy in predicting CO2 (R2 = 0.97) and H2S (R2 = 0.95) emissions from the MBBR. LSBoost also achieved the highest accuracy for predicting CO2 (R2 = 0.85) and H2S (R2 = 0.97) outlet concentrations from the aPBR. These findings underscore the importance of aligning AI algorithms to the characteristics of the treatment technology. The proposed AI models outperformed conventional statistical methods, demonstrating their ability to capture the complex, nonlinear dynamics typical of processes in environmental technologies. This study highlights the potential of AI-driven monitoring and control systems to significantly improve the efficiency of CCU biotechnologies in WWTPs for climate change mitigation and sustainable wastewater management.Item Open Access Circular bioeconomy and sustainable food systems: what are the possible mechanisms?(Elsevier, 2025-07-01) Nguyen, Thi Hoa; Wang, Xinfang; Utomo, Dhanan; Gage, Ewan; Xu, BingThe circular bioeconomy has emerged as a promising pathway for sustainable development, yet its specific role in fostering sustainable food systems remains underexplored. To our best knowledge, this study is the first systematic review to examine how the circular bioeconomy contributes to sustainable food practices. Using content analysis of 111 academic papers from SCOPUS database, we identify key mechanisms through which the circular bioeconomy enhances food safety and security. These include the development of innovative food products manufactured from bio-resources, the extension of product life through utilizing biodegradable films and bio-based compounds, and the improvement of food safety via sustainable packaging. Additionally, circular bioeconomy practices increase agricultural productivity by enhancing crop yields. From a corporate perspective, they optimize resource use, boost profitability, and generate new revenue streams from waste. Socially, these practices improve stakeholder wellbeing and generate employment opportunities. Environmentally, they support natural capital regeneration, reduce ecological footprints, and promote the sustainable use of resources. Despite these benefits, significant research gaps remain, particularly regarding the cross-sectoral relationships and multi-level impacts of circular bioeconomy practices. This study provides actionable implications for policymakers, practitioners, and researchers, emphasizing regulatory development, strategic decision making, and future research on corporate-level impacts.